Introduction

This storyboard delivers our final project product by visualizing Formula 1 Racing data focused on analyzing information on the drivers and different circuits.

Data showcase 1: Which factors are important to determine the best driver?

Multiple linear regression was utilized to determine which factors are important to evaluate the best driver.

Wins = b0 + (Pole Wins) X1 + (Total Points) X2 + (Fastest Laps) X3 + (Podiums) X4 + (1st WDC Age) X5 + e
Note: b0 is the intercept of the regression line and e is the model error (residuals) or the variation in the model

R^2 = 0.9904, p-value = 5.769e-06

All factors were significant except Fastest Laps and Age. Tried to evaluate the height factor, however, the p-value was truly not significant since the p-value was 0.72785.

The coefficient plot lists each of the coefficients and the effect they have on the model. The further away the point is from the dotted line set at zero, the larger of an impact there is.

Data showcase 2: Animated Plot of Career Total Wins for Top 10 Racers

Data showcase 3: Wins per team by track since 2006

Data showcase 4: Wins per driver since 2006

Data showcase 5: F1 WDC Racer Ages

Data showcase 6: Average Pit Stop Time from 2011-2021

Data showcase 7: Total points in 2021 for different racers

Data showcase 8: 2021 F1 Teams Total Points

Data showcase 9: 2021 US grand prix qualifying

These 2 graphs are created using the “f1dataR” library!

Data showcase 10: Fernando Alonso’s record breaking distance!

Data showcase 11: Frequency of Max Verstappen’s & Lewis Hamilton’s Finishing Positions

Data showcase 12: Most Wins for Each Racer at Various Circuits

Data showcase 13: Wins based on Started Grid Position

Data showcase 14: F1 WDC Racers and their Podium Wins